Conventionally, as this type of abnormality diagnosing technique, one is known that detecting a signal that represents sounds or a vibration generated by a sliding-rolling member or a sliding-rolling member related member of mechanical equipment; obtaining a frequency spectrum for the detected signal or an envelope signal thereof; extracting, from the frequency spectrum, only a frequency component that causes the abnormality of the sliding-rolling member of the mechanical equipment or the sliding-rolling member related member of the mechanical equipment; and employing the level of the extracted frequency component to diagnose the occurrence of the abnormality in the sliding-rolling member that is used in the mechanical equipment (see patent document 1).
Further, a technique is also known that detecting a sounds or a vibration generated by a rotary member or a rotary member related member; extracting, from the detected signal, a signal in a frequency band required for diagnosis; obtaining an envelope for the extracted signal; analyzing the frequency for the obtained envelope to obtain the level of the basic frequency component of a frequency, which causes the rotary member or the rotary member related member abnormality, and the natural number of times for the level of the frequency component; comparing the level of the basic frequency component with the level of the frequency component that is the natural number of times; and employing the comparison results as a reference for determining the mechanical equipment abnormality (see patent document 2).
Furthermore, a technique is known that an analog signal that indicates sounds or a vibration generated by mechanical equipment is converted into a digital signal through A/D (analog/digital) conversion, and actual digital data are generated; analysis processes, such as frequency analysis and envelope analysis, are performed for the actual digital data to generate actual frequency spectrum data; and the occurrence of the mechanical equipment abnormality is determined by examining whether a peak in the actual frequency spectrum data is present at the primary value (fundamental value), the secondary value and the quartic value of the frequency component that causes the mechanical equipment abnormality (see patent document 3).
Moreover, a technique is known that the envelope waveform of vibration acceleration is converted into a digital signal, and a vibration spectrum distribution is obtained digital vibration data per determined time, and at the same time, the rotational speed of a rolling bearing is obtained through the measurement of vibration; and when the time transient pattern of the rotational speed matches the time transient pattern of the frequency of the peak spectrum in the vibration spectral distribution, and when the frequency of the peak spectrum at an arbitrary time matches a characteristic frequency that is obtained based on the rotational speed of the rolling bearing and the geometric size of the rolling bearing and that causes the damage to the rolling bearing, it is assumed that damage to a specific portion of the rolling bearing has occurred (see patent document 4).
A method for detecting the peak of a frequency indicating an abnormality is not clearly described in these patent documents. However, when an abnormality, such as flaking of a bearing or eccentric displacement of the rotary shaft of a machine, has occurred, the peak of the frequency of a signal (abnormal signal) indicating this abnormality can be easily obtained by averaging the frequency spectrum. The averaging is a method that is regarded as effective for removing random noise and is used in the frequency analysis field, such as a Fast Fourier Transform (FFT) analysis.
Further, in these conventional techniques, the process (the envelope process) for obtaining an envelope signal is an analog process or a digital process, but the fast Fourier transform (FFT) process, which is a digital process, is employed for the frequency analysis. In order to perform the FFT operation, an A/D conversion is performed before or after the envelope process. And in either conventional technique, the FFT operation is performed immediately after the envelope process.
According to a system for performing the envelope process in a digital manner, an envelope process unit is required. Therefore, in order to reduce the cost and the size of the system, it is advantageous that the envelope process is performed in a digital manner.
For a system that performs the envelope process in a digital manner, an improvement of the efficiency of the FFT operation can be employed as a method for increasing the abnormality diagnosis efficiency. The improvement of the efficiency of the FFT operation can be achieved by reducing the number of points of the FFT operation.
Furthermore, an abnormality diagnosis apparatus that employs vibrations (including acoustic vibrations) is used to detect damage to an axle bearing or the wheels of a railway vehicle. Conventionally, in this type of abnormality diagnosis apparatus, a vibration sensor is provided for individual axle boxes, and damage to the axle boxes and the wheels is detected (see patent documents 5 and 6.
Conventionally, after a railway vehicle has been employed for a specific period of time, rotary parts, such as an axle bearing, are periodically inspected to determine whether an abnormality, such as a damage or abrasion, has occurred. This periodical inspection is performed by disassembling a mechanical device wherein rotary parts are assembled, so that, through visual inspection, a worker can find the damage and abrasion on the rotary parts. In the case of bearings, the main defects found during an inspection are, for example, indentations that bit a foreign substance, etc., flaking due to rolling contact fatigue and another abrasion; in the case of gears, example defects are fractures and abrasion of teeth; and in the case of wheels, example defects are abrasion, such as wheel flat. In any case, when roughness, abrasion, etc., which are not present with new parts, are found, the parts are exchanged for new ones.
However, the method that the entire mechanical equipment device is disassembled and a worker performs an inspection wither his or her eyes has the following problems. A great amount of labor is required for a disassembly operation for removing a rotary member and a sliding-rolling member from an apparatus, and an assembly operation for reassembling, with the apparatus, the rotary member and the sliding-rolling member that have been inspected, and maintenance costs for the apparatus would be considerably increased.
Further, during the reassembly process, the inspection could cause a defect in the rotary member or the sliding-rolling member, e.g., indentations that are not present before the inspection may be made in the rotary member or the sliding-rolling member. Furthermore, since multiple bearings are visually inspected within a limited period of time, defects may be missed. In addition, there are variations between individuals who judge a defect, and since parts are exchanged even though no defect found, an unnecessary cost is required.
Therefore, various methods that a rotary part abnormality can be diagnosed in an actual operating state while a mechanical apparatus in which rotary parts are mounted need not be disassembled have been proposed, (e.g., patent documents 1, 7 and 8). As the most common method, a method, as described in patent document 1, is that the vibration acceleration level of a bearing portion is measured by an accelerometer located at the bearing portion, and a FFT (Fast Fourier Transform) process is performed for the obtained signal to extract a signal that includes a frequency component at which a vibration is generated, so as to perform a diagnosis.
Moreover, for the rolling faces of the wheels of a railway vehicle, various methods have been proposed for detecting portions called flats. The flats are caused by friction or abrasion when the locking or skidding of wheels, relative to rails, has occurred due to an erroneous operation of the brakes, etc. (see, for example, patent documents 6, 9 and 10). Especially in patent document 6, an apparatus is proposed that employs a vibration sensor, a rotation measurement device, etc., to detect a defective state of the wheels of a railway vehicle and the rails along which trains pass.
Patent Document 1: JP-A-2003-202276
Patent Document 2: JP-A-2003-232674
Patent Document 3: JP-A-2003-130763
Patent Document 4: JP-A-09-113416
Patent Document 5: JP-A-4-235327
Patent Document 6: JP-A-9-500452
Patent Document 7: JP-A-2002-22617
Patent Document 8: JP-A-2004-257836
Patent Document 9: JP-A-4-148839
Patent Document 10: JP-A-2003-535755
However, since shock produced sounds and friction produced sounds tend to externally affect a vibration sensor and an acoustic sensor, and since acceleration due to turning motion affects a mobile member, abnormalities tend to be erroneously detected that are due to these unsteadying disturbances. Therefore, when the averaging calculation is frequently performed, in some cases, the frequency peak detection method using an averaging is not effective because the sensor is easily affected by a change in the speed and an external shocking sound, etc.
Furthermore, in a case where an abnormality has occurred for example, due to a small scratch, flaking, or rusting before the life has expired, the power of a signal output by a vibration sensor or an acoustic sensor is frequently so small that it is masked by mechanical noise or electrical noise. Therefore, at the abnormality prediction stage, before the life has expired, in many cases, a method for setting a threshold value and for extracting only a signal having a power greater than the threshold value can not be employed. The most difficult problem for a prediction of an abnormality is that when an S/N ratio of an abnormality signal, or a signal (abnormality prediction signal) that indicates a sign of an abnormality, to a noise signal is small, the noise signal may erroneously be regarded as an abnormality signal or an abnormality prediction signal. A procedure for avoiding the possibility an extremely small abnormality signal or an abnormality prediction signal will be missed can effectively increase the precision of an abnormality prediction for bearings, etc. However, when it is possible a noise signal will be erroneously determined to be an abnormality signal or an abnormality prediction signal, accordingly, the mechanical equipment must be frequently halted and inspected, so that the operating costs would be increased.
In addition, when reducing the number of points for the FFT operation in order to increase the calculation efficiency, the frequency resolution would be reduced, and the accuracy of an abnormality diagnosis would be deteriorated.
Further, for a system that performs the envelope process in a digital manner, an increase in the efficiency of a FFT operation can be employed as a method for improving the abnormality diagnostic efficiency, since an improvement in the efficiency of a FFT operation can be achieved by reducing the number of points for the FFT operation. However, were the efficiency of a calculation to be increased by reducing the number of points for a FFT operation, the frequency resolution would be reduced and the accuracy of an abnormality diagnosis would be deteriorated.
Small size and small power consumption are preferable for an operating device when it is mounted on a rotary machine, in order to diagnose abnormalities that are caused by bearing defects, etc. Further, from the viewpoint of calculation accuracy and from the viewpoint of memory capacity, it is desired that a FFT operation be performed by using only a small number of operation points. On the contrary, as described above, the accuracy of an abnormality diagnosis is reduced, to a degree, when the frequency resolution is not high enough. But when the frequency level at which a raw waveform can be recovered must be set as 10 kHz (so that the sampling frequency is equal to or higher than 20 kHz), in the long run, the upper limit for the defective frequency of a bearing will be equal to or lower than 1 kHz.
However, for a conventional abnormality diagnosis apparatus, since a vibration sensor must be provided for each axle box, there are the following problems. The number of sensors to be installed must be increased for each vehicle, the number of input circuits and the number of lines must be increased for a signal processor that processes sensor signals, and the structure of the circuit becomes complicated.
However, as one problem for the defective state detection apparatus described in patent document 6, abnormal vibrations can not be identified to determine whether they are caused by flat wheels, by axle bearings, by abnormalities along the rails or by other abnormalities.